Falls, Balance and Injury Research Centre, Neuroscience Research Australia, Barker Street, Randwick, NSW 2031, Australia.
Falls, Balance and Injury Research Centre, Neuroscience Research Australia, Barker Street, Randwick, NSW 2031, Australia; School of Public Health and Community Medicine, UNSW, Kensington, NSW 2033, Australia.
J Clin Epidemiol. 2016 Nov;79:62-69. doi: 10.1016/j.jclinepi.2016.04.004. Epub 2016 Apr 19.
To translate, validate, and compare performance of an International Classification of Diseases, 10th revision (ICD-10) version of the Multipurpose Australian Comorbidity Scoring System (MACSS) against commonly used comorbidity measures in the prediction of short- and long-term mortality, 28-day all-cause readmission, and length of stay (LOS).
Hospitalization and death data were linked for 25,374 New South Wales residents aged 65 years and older, admitted with a hip fracture between 2008 and 2012. Comorbidities were identified according to the MACSS, Charlson, and Elixhauser definitions using ICD-10 coding algorithms. Regression models were fitted and area under the curve (AUC) and Akaike Information Criterion assessed.
The ICD-10 MACSS had excellent discriminating ability in predicting inhospital mortality (AUC = 0.81) and 30-day mortality (AUC = 0.80), acceptable prediction of 1-year mortality (AUC = 0.76) but poor discrimination for 28-day readmission and LOS. The MACSS algorithm provided better model fit than either Charlson or Elixhauser algorithm for all outcomes.
This work presents a rigorous translation of the ICD-9 MACSS for use with ICD-10 coded data. The updated ICD-10 MACSS outperformed both Charlson and Elixhauser measures in an older population and is recommended for use with large administrative data sets in predicting mortality outcomes.
将多功能澳大利亚合并症评分系统（MACSS）的国际疾病分类第 10 版（ICD-10）版本翻译成简体中文，并与常用合并症测量方法进行比较，以预测短期和长期死亡率、28 天全因再入院率和住院时间（LOS）。
2008 年至 2012 年间，对新南威尔士州 25374 名 65 岁及以上髋部骨折住院患者进行了住院和死亡数据链接。根据 MACSS、Charlson 和 Elixhauser 定义，使用 ICD-10 编码算法确定合并症。拟合回归模型，并评估曲线下面积（AUC）和赤池信息量准则。
ICD-10 MACSS 在预测住院内死亡率（AUC=0.81）和 30 天死亡率（AUC=0.80）方面具有出色的区分能力，对 1 年死亡率的预测能力尚可（AUC=0.76），但对 28 天再入院和 LOS 的区分能力较差。对于所有结局，MACSS 算法提供的模型拟合优于 Charlson 或 Elixhauser 算法。
这项工作对用于 ICD-10 编码数据的 ICD-9 MACSS 进行了严格的翻译。在老年人群中，更新后的 ICD-10 MACSS 在预测死亡率方面优于 Charlson 和 Elixhauser 指标，建议在使用大型行政数据集预测死亡率时使用。
